| 84 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00035920657 |
| 320 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00021128745 |
| 405 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.00019020138 |
| 453 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.0001801482 |
| 508 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00017108973 |
| 983 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00012677179 |
| 1,064 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00012181459 |
| 1,444 |
Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities |
2019 |
SIGMOD |
0.00010616242 |
| 1,541 |
Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses |
2018 |
VLDB |
0.00010288394 |
| 1,583 |
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries |
2020 |
SIGMOD |
0.00010148362 |
| 1,740 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
9.7289523e-05 |
| 2,009 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
9.1813272e-05 |
| 2,228 |
Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models |
2017 |
VLDB |
8.7912743e-05 |
| 2,348 |
Learned Cardinality Estimation: An In-depth Study |
2022 |
SIGMOD |
8.5910072e-05 |
| 2,523 |
Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation |
2022 |
VLDB |
8.3316032e-05 |
| 2,584 |
Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation |
2021 |
VLDB |
8.2435322e-05 |
| 2,852 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
7.9201312e-05 |
| 2,987 |
Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs |
2022 |
VLDB |
7.767043e-05 |
| 3,060 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
7.6828463e-05 |
| 3,093 |
Correlation Sketches for Approximate Join-Correlation Queries |
2021 |
SIGMOD |
7.6378811e-05 |
| 3,136 |
Every Row Counts: Combining Sketches and Sampling for Accurate Group-By Result Estimates |
2019 |
CIDR |
7.5902303e-05 |
| 3,212 |
Efficiently Approximating Selectivity Functions using Low Overhead Regression Models |
2020 |
VLDB |
7.5145409e-05 |
| 3,555 |
Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning |
2021 |
VLDB |
7.1877332e-05 |
| 3,740 |
FACE: A Normalizing Flow based Cardinality Estimator |
2022 |
VLDB |
7.0398782e-05 |
| 3,995 |
Simplicity Done Right for Join Ordering |
2021 |
CIDR |
6.8530469e-05 |
| 4,329 |
MNC: Structure-Exploiting Sparsity Estimation for Matrix Expressions |
2019 |
SIGMOD |
6.64569e-05 |
| 4,725 |
Scalable Reservoir Sampling on Many-Core CPUs |
2019 |
SIGMOD |
6.4337491e-05 |
| 5,029 |
COMPASS: Online Sketch-based Query Optimization for In-Memory Databases |
2021 |
SIGMOD |
6.2952031e-05 |
| 5,245 |
FASTgres: Making Learned Query Optimizer Hinting Effective |
2023 |
VLDB |
6.1995935e-05 |
| 5,522 |
Density-optimized Intersection-free Mapping and Matrix Multiplication for Join-Project Operations |
2022 |
VLDB |
6.0818991e-05 |
| 5,717 |
Combining Sampling and Synopses with Worst-Case Optimal Runtime and Quality Guarantees for Graph Pattern Cardinality Estimation |
2021 |
SIGMOD |
6.0067263e-05 |
| 5,841 |
Joins on Samples: A Theoretical Guide for Practitioners |
2020 |
VLDB |
5.9569427e-05 |
| 6,672 |
Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation |
2023 |
SIGMOD |
5.6975871e-05 |
| 6,812 |
dbET: Execution Time Distribution-based Plan Selection |
2023 |
SIGMOD |
5.6597129e-05 |
| 6,840 |
ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation |
2024 |
SIGMOD |
5.6513231e-05 |
| 7,666 |
Disclosure-Compliant Query Answering |
2024 |
SIGMOD |
5.4565877e-05 |
| 7,902 |
Identifying Insufficient Data Coverage in Databases with Multiple Relations |
2020 |
VLDB |
5.4135994e-05 |
| 7,975 |
Robust Query Processing: Mission Possible |
2020 |
VLDB |
5.3985544e-05 |
| 8,154 |
Thrifty Query Execution via Incrementability |
2020 |
SIGMOD |
5.3732833e-05 |
| 8,188 |
Efficient Query Re-optimization with Judicious Subquery Selections |
2023 |
SIGMOD |
5.3649397e-05 |
| 8,363 |
alpha to omega: The Greek Alphabet of Sampling |
2020 |
CIDR |
5.3305234e-05 |
| 9,141 |
Presto’s History-based Query Optimizer |
2024 |
VLDB |
5.2078543e-05 |
| 9,667 |
Small Selectivities Matter: Lifting the Burden of Empty Samples |
2021 |
SIGMOD |
5.1278365e-05 |
| 9,995 |
Graph Transformers for Query Plan Representation: Potentials and Challenges |
2025 |
VLDB |
5.0845476e-05 |
| 10,045 |
Agile-Ant: Self-managing Distributed Cache Management for Cost Optimization of Big Data Applications |
2024 |
VLDB |
5.0786422e-05 |
| 10,257 |
PRICE: A Pretrained Model for Cross-Database Cardinality Estimation |
2025 |
VLDB |
5.039379e-05 |
| 10,370 |
An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL |
2025 |
SIGMOD |
5.0010514e-05 |
| 10,500 |
Bridging the Gap: Cardinality Estimation for Semantic Queries on Unstructured Data |
2026 |
SIGMOD |
4.9605343e-05 |
| 10,699 |
CorrBound: Cardinality Estimation Accounting for Inter- and Intra-relation Correlations |
2026 |
SIGMOD |
4.9605343e-05 |
| 10,745 |
Qualitative Join Discovery in Data Lakes using Examples |
2026 |
SIGMOD |
4.9605343e-05 |